Abstract
Assessing the quality of groundwater is important to ensure sustainable safe use of these resources. However, describing the overall water quality condition is difficult due to the spatial variability of multiple contaminants and the wide range of indicators (chemical, physical and biological) that could be measured. This contribution proposes a GIS-based groundwater quality index (GQI) which synthesizes different available water quality data (e.g., Cl−, Na+, Ca2+) by indexing them numerically relative to the World Health Organization (WHO) standards. Also, introduces an objective procedure to select the optimum parameters to compute the GQI, incorporates the aspect of temporal variation to address the degree of water use sustainability and tests the sensitivity of the proposed model. The GQI indicated that the groundwater quality in the Nasuno basin, Tochigi Prefecture, Japan, is generally high (GQI <90). It has also displayed the natural (depth to groundwater table, geomorphologic structures) and/or anthropogenic (land-use and population density) controls over the spatial variability of groundwater quality in the basin. Temporally, groundwater quality is more variable in the upper and lower parts of the basin (variation, V, 15–30%) compared to the middle part (V, <15%) probably attributed to the seasonality of precipitation and irrigation of rice. In the lower southeastern part of the Nasuno basin and the vicinity of the Naka and Houki rivers the sustainable use of groundwater is constrained by the relatively low and variable groundwater quality. The model sensitivity analysis indicated that parameters which reflect relatively lower water quality (high mean rank value) and those of significant spatial variability imply larger impacts on the GQI and must be carefully and accurately mapped. Optimum index factor technique allows the selection of the best combination of parameters dictating the variability of groundwater quality and enables an objective and fair representation of the overall groundwater quality.
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References
Aller L, Bennet T, Leher JH, Petty RJ, Hackett G (1987) DRASTIC: A standardized system for evaluating ground water pollution potential using hydrogeological settings. Environmental Protection Agency, EPA 600/2-87-035; pp 622
Babiker IS, Hiyama T, Moahmed MAA (2005) Variability of groundwater quality in the alluvial Nasuno basin, Tochigi Prefecture, Japan. App Geochem. (under review)
Barber C, Bates LE, Barron R, Allison H (1993) Assessment of the relative vulnerability of groundwater to pollution: a review and background paper for the conference workshop on vulnerability assessment. J Aust Geol Geophys 14(2/3):1147–1154
Bonham-Carter GF (1996) Geographic information systems for geoscientists: modeling with GIS computer methods in the geosciences, vol 13. Elsevier Science Ltd, Pergamon, pp 1–50
Choi MW (1976) A hydrological study of the groundwater in Nasu, Tochigi Prefecture. The Tokyo Press, Tokyo, pp 21–39
Chung CF, Fabbri AG (2001) Prediction models for landslide hazard using a Fuzzy set approach. In: Marchetti M, Rivas V (eds) Geomorphology & environmental impact assessment. Balkema, Rotterdam, The Netherlands (in press)
Hiyama T, Suzuki Y (1991) Groundwater in the Nasuno basin — Spatial and seasonal changes in water quality (in Japanese), Hydrol. J Jap Assoc Hydro Scs 21(3):143–154
ITC-ILWIS (2001) Ilwis 3.0 academic user's guide. International Institute for Aerospace Survey and Earth Sciences (ITC), The Netherlands, pp 428–456
Levallois P, Theriault M, Rouffignat J, Tessier S, Landry R, Ayotte P, Girard, M, Gingras S, Gauvin D, Chiasson C (1998) Groundwater contamination by nitrates associated with intensive potato culture in Quebec. Sci Tot Enviro 217:91–101
Lodwick WA, Monson W, Svoboda L (1990) Attribute error and sensitivity analysis of map operations in geographical information systems: Suitability analysis, Inter J Geogr Inform Systems 4(4):413–428
Melloul A, Collin M (1994) Water quality factor identification by the ‘Principal Components’ statistical method. Water Sci Technol 34:41–50
Napolitano P, Fabbri AG (1996) Single-Parameter sensitivity analysis for aquifer vulnerability assessment using DRASTIC and SINTACS. HydroGIS 96: Application of geographical information systems in hydrology and water resources management (Proceedings of Vienna Conference), IAHS Pub, No. 235, pp 559–566
Ohashi M, Tase N, Hiyama T,Suzuki Y (1994) Temporal and spatial changes of nitrate concentration of groundwater in the Nasuno Basin (in Japanese). Hydrol (J Japa Assoc Hydro Scs) 24(4):221–232
Praharaj T, Swain SP, Powell MA, Hart BR, Tripathy S (2002) Delineation of groundwater contamination around an ash pond Geochemical and GIS approach. Environ Int 27:631–638
Robins NS (2002) Groundwater quality in Scotland: major ion chemistry of the key groundwater bodies. Sci Tot Envir 294(1–3):41–56
Rosen L (1994) A study of the DRASTIC methodology with emphasis on Swedish conditions. Gr Water 32(2):278–285
Vrba J, Zoporozec A (1994) Guidebook on mapping groundwater vulnerability, IAH International Contribution for Hydrogeology, vol 16. Heise, Hannover, pp 131
WHO, World Health Organization (2004) Guidelines for drinking-water quality, vol 1, 3rd edn, recommendations. WHO, Geneva, Switzerland, pp 145–220
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Babiker, I.S., Mohamed, M.A.A. & Hiyama, T. Assessing groundwater quality using GIS. Water Resour Manage 21, 699–715 (2007). https://doi.org/10.1007/s11269-006-9059-6
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DOI: https://doi.org/10.1007/s11269-006-9059-6